New Perspectives on Recommender Systems for Industries

Mouzhi Ge, G. Pilato, Fabio Persia, D. D’Auria
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引用次数: 1

Abstract

Nowadays, recommender systems are increasingly being exploited in many industrial applications, including virtual museums and movie streaming platforms. In the last few years, some new perspectives provided by research paradigms such as deep learning or quantum computing, have arisen. As a result, this paper identifies four new perspectives on recommender systems: e-health, tourism, deep-learning-based, and recommender systems exploiting quantum computing. After discussing them, the paper provides the current state of the art and highlights the possible future directions for industries.
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工业推荐系统的新视角
如今,推荐系统越来越多地应用于许多工业应用,包括虚拟博物馆和电影流媒体平台。在过去几年中,深度学习或量子计算等研究范式提供了一些新的视角。因此,本文确定了推荐系统的四个新视角:电子医疗、旅游、基于深度学习的推荐系统和利用量子计算的推荐系统。在讨论它们之后,本文提供了当前的艺术状态,并强调了行业可能的未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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